Google Cloud Results

Increases book sales for publishers by optimizing search results on retail sites

The best book you’re looking to read is out there, just waiting for you to find it. Publishers want to make this as easy as possible for you. But when searching on their favorite retailers’ websites, many people miss titles completely. Why? Because people of course search using phrases that make sense to them—which are often not the same phrases supplied by publishing marketers.

As it turns out, more people search for books using keywords such as “sad story,” “bad guys,” “real life,” or “ya dystopian novel” rather than more academic phrases such as “character-driven storyline,” “compelling writing style,” or “wistful poetry,” according to research from Kadaxis, a New York-based data science company.

Kadaxis wants to turn this lose-lose situation into a win-win. By optimizing metadata and developing APIs for audience analysis, text classification, and manuscript assessment, Kadaxis matches the right books to the right readers. When its publisher customers submit their optimized keywords for each book to major e-commerce sites, they’re much more likely to drive sales.

“Google Cloud Platform offers competitive pricing and flexible per-second billing, reducing our overall cloud hosting costs by 10%. We also get 20% better network performance compared to our previous cloud providers, which helps because we pull a lot of data from different sources.”

—Chris Sim, Founder and CEO, Kadaxis

Kadaxis provides a much-needed service. As book sales have shifted online, the overall market has encountered challenges, despite the growing number of books published. U.S. publishing industry sales have been flat or falling every year for the past decade, according to the Association of American Publishers. Kadaxis could potentially change that—but only if its service can scale for big data.

Understanding how people consume and search for books is challenging, and the intelligence Kadaxis provides doesn’t come easy. For each of the thousands of titles it optimizes, Kadaxis crawls book reviews, social media discussions, and anywhere else people talk about books, gathering anonymous consumer signals. It then uses machine learning to analyze those signals and provide a rich set of audience-driven keywords that make the book more likely to appear in a search.

For its service to be viable, Kadaxis requires cost-effective compute on demand, as well as a robust network to move big data. To improve scalability, economics, and performance, Kadaxis abandoned a multi-cloud strategy in favor of Google Cloud Platform, consolidating onto Google Compute Engine for high-performance, scalable virtual machines (VMs).

“Our publisher customers come to us with as many as 20,000 titles at once. Google Compute Engine allows us to optimize keywords quickly, so our customers notice immediate and significant increases in sales.”

—Chris Sim, Founder and CEO, Kadaxis

Serving large publishers

A single publisher can have thousands of titles for Kadaxis to optimize. With Google Compute Engine, Kadaxis can easily scale to meet any publisher’s need, using custom machine types to get the best performance without wasting money on unnecessary resources.

“Our publisher customers come to us with as many as 20,000 titles at once,” says Chris. “Google Compute Engine allows us to optimize keywords quickly, so our customers notice immediate and significant increases in sales.”

More secure collaboration

Kadaxis launched its business on G Suite, using cloud-based apps such as Gmail, Google Docs, Drive, Sheets, and Slides to keep the startup company connected and productive across time zones. To maintain strong security, the company uses two-step verification with USB Security Keys. With no infrastructure to maintain or software to administer, Kadaxis can focus on moving its core business forward.

“We run a lean team and we need a lot of flexibility from our productivity tools,” says Chris. “G Suite is essential for us to work remotely with a distributed team. It’s the gold standard.”

“Leveraging Google Cloud Platform services and machine learning APIs will help us connect more readers with more books by running experiments faster and more cost effectively. For any new research we do, we will look to Google first instead of building the infrastructure ourselves.”

—Chris Sim, Founder and CEO, Kadaxis

A cloud foundation for AI

Kadaxis took home the 2016 BookTech Company of the Year Award, increasing visibility and demand for its service. Although the company faces the same challenges as any growing business, scaling its technology has not been a problem.

“Leveraging Google Cloud Platform services and machine learning APIs will help us connect more readers with more books by running experiments faster and more cost effectively,” says Chris. “For any new research we do, we will look to Google first instead of building the infrastructure ourselves.”

About Kadaxis

Kadaxis uses data science to improve book discovery across the publishing value chain. Its flagship Keyword Analysis product improves the visibility of books in retailer search.